front.py2pydantic

How do we eliminate some of the boilerplate between having python functions and making them pydantic?

>>> from i2.tests.objects_for_testing import formula1
>>> pyd_input_model = func_to_pyd_input_model_cls(formula1)
>>> pyd_input_model
<class 'pydantic.main.formula1'>
>>> from i2 import Sig
>>> Sig(formula1)
<Sig (w, /, x: float, y=1, *, z: int = 1)>
>>> Sig(pyd_input_model)
<Sig (*, w: Any, x: float, z: int = 1, y: int = 1) -> None>

>>> pyd_func = func_to_pyd_func(formula1)
>>> input_model_instance = pyd_input_model(w=1, x=2)
>>> input_model_instance
formula1(w=1, x=2.0, z=1, y=1)
>>> pyd_func(input_model_instance)
3.0
>>> formula1(1, x=2)  # can't say w=1 because w is position only
3

front.py2pydantic.func_to_pyd_func(func: Callable, dflt_type=typing.Any)

Get a ‘opyrator’ function from a python function. That is, a function that has a single pydantic model input and output.

front.py2pydantic.func_to_pyd_input_model_cls(func: Callable, dflt_type=typing.Any, *, name=None, warn_when_changing_names=True)

Get a pydantic model of the arguments of a python function

>>> def foo(a, b: int, c: bool=False):
...     ...
>>> obj = func_to_pyd_input_model_cls(foo)
>>> import json
>>> assert json.loads(obj.schema_json()) == (
... {
...     'title': 'foo',
...     'type': 'object',
...     'properties': {
...         'a': {'title': 'A'},
...         'b': {'title': 'B', 'type': 'integer'},
...         'c': {'title': 'C', 'default': False, 'type': 'boolean'}
...     },
...     'required': ['a', 'b']
... })

If some argument names of the function conflict with attribute names of BaseModel, these will be capitalized to resolve the conflict.

>>> def bar(x, copy, schema):
...     ...
>>> obj2 = func_to_pyd_input_model_cls(bar, warn_when_changing_names=False)
>>> assert json.loads(obj2.schema_json()) == (
... {
...     'title': 'bar',
...     'type': 'object',
...     'properties': {
...         'x': {'title': 'X'},
...         'COPY': {'title': 'Copy'},
...         'SCHEMA': {'title': 'Schema'}},
...     'required': ['x', 'COPY', 'SCHEMA']
... })

front.py2pydantic.func_to_pyd_model_specs(func: Callable, dflt_type=typing.Any)

Helper function to get field info from python signature parameters